Перегляд за Автор "Yanko, Alina"

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    Mathematical Model of the Process of Raising Integers to an Arbitrary Power of a Natural Number in the System of Residual Classes
    (Igor Sikorsky Kyiv Polytechnic Institute, 2023) Krasnobayev, Victor; Yanko, Alina; Kovalchuk, Dmytro
    It is known that the use of a non-positional number system in residual classes (SRC) in computer systems (CS) can significantly increase the speed of the implementation of integer arithmetic operations. The use of such properties of a non-positional number system in the SRC as independence, equality and low-bitness (low-digit capacity) of the residues that define the non-positional code data structure of the SRC provides high user performance for the implementation in the CS of computational algorithms consisting of a set of arithmetic (modular) operations. The greatest efficiency from the use of the SRC is achieved when the implemented algorithms consist of a set of arithmetic operations such as addition, multiplication and subtraction. There is a large class of algorithms and tasks (tasks of implementing cryptoalgorithms, optimization tasks, computational tasks of large dimension, etc.), where, in addition to performing integer arithmetic operations of addition, subtraction, multiplication, raising integers modulo and others in a positive numerical range, there is a need to implement the listed above arithmetic and other operations, in the negative numerical range. The need to perform these operations in a negative numerical range significantly reduces the overall efficiency of using the SRC as a number system of the CS. In this aspect, the lack of a mathematical model for the process of raising integers in the SRC in the negative numerical region makes it difficult to develop methods and procedures for raising integers to an arbitrary power of a natural number in the SRC, both in positive and negative numerical ranges. The purpose of the article is the synthesis of a mathematical model of the process of raising integers to an arbitrary power of a natural number in the SRC, both in positive and negative numerical ranges.
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    Modern methods for protecting and storing data in computer systems to ensure their fault tolerance
    (Igor Sikorsky Kyiv Polytechnic Institute, 2024) Yanko, Alina; Mychailichenko, Oleksii; Hlushko, Alina
    The study's relevance stems from the fact that, in today’s world, where digital technologies permeate all areas of life and cyber threats continuously adapt, traditional methods of identifying critical vulnerabilities that rely on internal data often lag behind the evolution of these threats, leaving computer systems critically vulnerable. Ensuring the fault tolerance of computer systems is essential for stability and protection against such threats. The research methodology includes analyzing modern approaches to ensuring fault tolerance in relation to both hardware and software, utilizing cybersecurity models, redundancy, and data integrity at both the routing and system levels. Reliability was evaluated through theoretical analysis and application of existing technologies, as well as analysis of available system failure statistics based on open data sources. The main goal of the research was to develop recommendations and practical solutions to enhance the fault tolerance of computer systems through the integration of software and hardware protection methods based on an analysis of existing solutions. The task was to ensure system resilience to hardware-software failures before, during, and after their occurrence, thereby minimizing downtime of the hardware-software complex and data loss. The research demonstrated that a comprehensive approach provides the best protection, with the ability to identify issues before they arise. This includes component redundancy of both software and hardware types and the implementation of diagnostic and predictive failure systems. Systems equipped with modern anomaly detection methods can respond much faster to potential threats and minimize losses, while hardware systems with active monitoring and automatic switchover to backup components ensure continuity of processes in the event of critical technical failure. Future technologies, such as using artificial intelligence to analyze system state and predict potential failures, will significantly increase the efficiency and protection of hardware-software systems. However, they currently face compatibility challenges when combined with both legacy and new equipment, limiting their widespread adoption. The results of the research show that systems utilizing a hybrid monitoring approach, combining software and hardware protection, better adapt to changing operating conditions and demonstrate higher fault tolerance.